What we believe

What we believe

"Here's to the crazy ones. The misfits, the rebels, the troublemakers, the round pegs in the square holes, the ones who see things differently. They're not fond of rules, and they have no respect for the status quo. You can quote them, disagree with them, glorify or vilify them. About the only thing you can't do is ignore them. Because they change things - they push the human race forward. And while some may see them as the crazy ones, we see genius. Because the people who are crazy enough to think they can change the world, are the ones who do." --Steve Jobs

CogAI4Sci team

CogAI4Sci team

Our Cognitive AI for Science (CogAI4Sci) team at National University of Singapore focuses on developing novel AI algorithms solve real-world problems in biomedical sciences using inspiration from human cognition.

Before starting CogAI4Sci team, Dianbo Liu was a group leader at the Broad Institute of MIT and Harvard. Prior to the Broad Institute, Dianbo worked as a postdoctoral researcher with Prof. Yoshua Bengio (a Turing Award winner) and led the Humanitarian AI team at the Mila-Quebec AI Institute. This followed his fellowship training and studies in medical informatics at Harvard Medical School. Dianbo earned his PhD from the University of Dundee, Scotland, under the supervision of Prof. Timothea Newman. During his doctoral studies,he received the Vest Scholarship from the Massachusetts Institute of Technology (MIT) and was a special graduate student at the MIT Computer Science and Artificial Intelligence Lab. Dianbo also co-founded two start-ups, "GeneTank" and "SecureAILabs," to advance AI applications in biomedical sciences during his training.

Research aims

Research aims

We are a machine learning algorithm team working on "A,B,C", where:

We develop machine learning agents that autonomously make scientific discoveries by generating hypotheses, designing experiments, and interpreting results.

We address real-world problems in biomedical sciences aims to build a comprehensive 'world model' of the human body, from the molecular and cellular levels to the organ level, and ultimately to the entire body.

Our ultimate question is what differentiates human intelligence from that of other species in the evolutionary process, and how this knowledge can be used to build self-aware AI capable of learning, training, understanding, and creating independently of human intervention.

One key distinction between Homo sapiens and other species is the use of discrete symbols. Therefore, in recent years, our team has focused on understanding, optimizing, and applying discrete compositional representations to address generalization and reasoning challenges in machine learning.

Team

Team

Abhijeet Sinha (PhD candidate, previous: IIT, Madras, India)

Arash Lagzian(Visiting Scholar from Iran)

Anirudh Prabhakaran (Intern from NIT,India. )

Chengbo Li(Intern, From UIUC, USA.)

Dianbo Liu (Principal investigator)

Hongyu He (PhD candidate. Previous: Duke U., USA.)

Mike Zhu(co-adv. PhD candidate with Prof.Yue Li at McGill)

Nirlipta Pande (intern, from BITS, Pilani, India)

Peisong Zhang (master student at NUS)

Qiran Zou (PhD candicate previous: Tsinghua U, China)

Qifei Wang (Visiting scholar from Chinese Academy of Sciences)

Rushi Shah (Intern, from IIT, Jodhpur, India.)

Samson Yu Bai Jian (PhD candidate, Previous: NUS,Singapore)

Srinivas Anumasa (Postdoc researcher. Previous: IIT Hyderabad, India. )

Ting Xu (Postdoc, co-advised with Prof. Ching-Yu Cheng. Previous: USTC,China)

Tingting Chen (PhD candidate. Previous: UNSW,Australia.)

Wenhao Zhao (PhD candidate. Previous: Beihang U,China. )

Xuming Ran (PhD candidate. Previous:Shanghai AI lab and CQJT U,China)

Xianrui He (Master's student at NUS)

Yiming Tang(PhD candidate. Previous: Peking U, China.)

Yuxuan Wu (Visiting scholar from Shanghai Maritime U, China.)

Yizhen Liao (Intern from Tsinghua U, China.)

Zarif Ikram （Visiting scholar from Bangladesh University of Engineering and Technology. )

Zarif Bin Akhtar （Intern from American International University-Bangladesh. )

Zexian Wang （Intern from Tsinghua U/UMichigan )

Zhiwei Xue （rotation PhD student, NUS, Previous: U. Michigan,USA )

Sankepally Sainath Reddy (Intern, from IIIT-RAIPUR ,India. Next: back to India)

Trang Nguyen Ngoc Phuong (Graduate research asssitant, previously Mila Canada , Next: PhD at Stanford)

AmirHossein Alamdar (Intern from Sharif Technology Uni., Iran Next: back to Sharif )

Aryan Amit Barsainyan (intern from NITK, India Next: back to NITK )

Zhixuan Xiao （visiting scholar from Tsinghua Uni., China. Next: back to Tsinghua )

Jiawei Wu (Intern, from Huadong Normal Uni.,China. ), Next:

Mingyuan Yan (Graduate research asistant. From Huadong Normal Uni.,China. ), Next:

Xiaoye Wang (Intern, Harbin Institute of Tech.,China. Next: Cambridge Uni. )

Uma Kadam (Intern, from IIIT Guwahati, India. Next: Microsoft )

Abhinav_Sharma (Intern, from IIIT Guwahati, India. Next: back to Inida )

Manvith Prabhu (Intern, from NITK, India. Next: back to Inida )

Taoyong Cui (Intern from Tsinghua University, China. Next: back to Tsinghua)

Anhying Bai (Intern, from Tsinghua University, China. Next: back to Tsinghua)

Zheqi Liu (From Tsinghua Uni.,China. Intern. Next: UCSD)

Maab Elrashid (From Sudan. Mentee at Mila-Quebec AI institute, with Prof. Yoshua Bengio. Next: Mila)

Ziqing Mai(From Tsinghua University, China. Intern. Next: back to Tsinghua)

Zile Yang(Intern, from Huazhong tech University, China. Next: back to Huangzhong )

Yice Fang(From Tsinghua University, China. Intern. Next: back to Tsinghua)

Bonaventure F. P. Dossou (Mentee at Mila-Quebec AI institute. next: PhD at McGill )

Rulin Shao (Mentee at MIT/Harvard, Next graduent student at CMU/ Amazon, now PhD at UW)

Loïc Kwate Dassi (Mentee at Mila-Quebec AI institute, Next: DeepMind London )

Oussama Boussif, Mentee at Mila. Next: PhD with Yoshua Bengio at Mila )

Li Huang (Mentee at Harvard. Next: PhD at Tsinghua. Now: faculty at Chinese Academy of Medical Sciences & Peking Union Medical College )

James Assiene (Mentee at Mila-Quebec AI institute. Next: DeepMind London )

Tianyi Zhang (Mentee at Harvard. Next: PhD at ASU )

Léna Néhale Ezzine,Mentee at Mila. Next: PhD with Yoshua Bengio at Mila )

Wisdom d'Almeida (Mentee at Mila-Quebec AI institute. Next: researcher at Miscrosoft/PhD at Oxford )

Jiahe Tian (Mentee at Harvard. Next: graduent student at CMU )

Ruobin Tao(Mentee in Boston, now at University of New South Wales, Australia )

Yuhao Qian (Mentee in Boston. Next: Amazon )

Pascal Junior Tikeng Notsawo (Mentee at Mila-Quebec AI institute. Next: PhD at Mila )

Leyu Dai (Mentee at Harvard. Next: PhD at University of North Carolina at Chapel Hill )

Junfeng Zhi (Mentee at Harvard. Next: graduent student at Duke. Now: engineer at Amazon )

Brice Nanda (Mentee at Mila-Quebec AI institute. Next:Msc at Mila )

Yihe Yang (Mentee at Harvard. Next:Msc at CMU )

Zhuang Ma (Mentee at Harvard. Next: graduent student at CMU )

News

News

  • [June 2024] Our work on self-supervised learning on medical data BarlowTwins-CXR is published on BMC. Congratulatiosn to Haoyue and all co-authors.
  • [Nov 2023] Our exploration of generative models for causal discovery of gene networks Swift-DynGFN is accepted at Neurips Generative model for biology workshop. Congratulatiosn to Trang and all co-authors.
  • [Nov 2023] Make our large language model physical reasoning task COAT is available
  • [June. 2023] Our 2-year effort on attention schema will be presented at Neurips InforCog workshop
  • [Apr. 2023] Present our SAF paper at ICLR 2023 at Kigali, Rwanda
Join our team

Join our team

We have multiple openings for PhD students, postdocs, interns and visiting scholars to join our lab and work with us together in the following directions:

  • AI scientist for medicine and biology
  • Discrete representation for large language models and diffusion
We welcome any candidate who dares to think big, sees things differently and is not fond of rules, regardless of their gender, religion, race, age, national origin,disability or which universities they graduate from. If you are interested, please fill in this form AND send me an email at

dianbo at nus dot edu dot sg

Publications

Publications

For the most up-to-date list of publications, see my Google Scholar profile.

Selected Machine learning Publications

GFlowOut: Dropout with Generative Flow Networks
Dianbo Liu , Moksh Jain, Bonaventure Dossou, Qianli Shen, Salem Lahlou, Anirudh Goyal, Nikolay Malkin, Chris Emezue, Dinghuai Zhang, Nadhir Hassen, Xu Ji, Kenji Kawaguchi, Yoshua Bengio
ICML 2023
Stateful active facilitator: Coordination and Environmental Heterogeneity in Cooperative Multi-Agent Reinforcement Learning
Dianbo Liu, Vedant Shah,Oussama Boussif, Anirudh Goyal, Michael Curtis Mozer,Nicolas Heessm Yoshua Bengio.
ICLR 2023
Discrete- Valued Neural Communication
Dianbo Liu, Alex Lamb, Kenji Kawaguchi, Anirudh Goyal, Chen Sun, Michael Curtis Mozer, Yoshua Bengio
Neurips 2021

Selected Machine learning for biomed Publications

Machine learning approaches to predicting no-shows in pediatric medical appointment
Dianbo Liu, Won-Yong Shin, Eli Sprecher, Kathleen Conroy, Omar Santiago, Gal Wachtel, Mauricio Santillana
NPJ digital medicine 2022
ENCODE Phase III: Building an Encyclopedia of Candidate cis-Regulatory Elements for Human and Mouse
Jill Moore1, Michael J. Purcaro , Bradley E. Bernstein. . . Dianbo Liu. . . .. Barbara Wold, Ross C. Hardison , al.
Nature 2020
Integrative construction of regulatory region networks in 127 human reference epigenomes by matrix factorization
Dianbo Liu, Jose Davila-Velderrain, Zhizhuo Zhang, Manolis Kellis al.
Nucleic acids research 2019
Get in Touch

Contact

dianbo at nus dot edu dot sg

Level 13
12 Science Drive 2, Singapore 117549